Accelerating Homomorphic Computations on Rational Numbers

DOI10.1007/978-3-319-39555-5_22zbMath1346.68087OpenAlexW2492687001MaRDI QIDQ2822686

Frederik Armknecht, Angela Jäschke

Publication date: 4 October 2016

Published in: Applied Cryptography and Network Security (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-39555-5_22

zbMATH Keywords

implementationencodingfully homomorphic encryptionconfidential machine learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Data encryption (aspects in computer science) (68P25)

Related Items (2)

Unsupervised Machine Learning on encrypted data ⋮ Encoding of Rational Numbers and Their Homomorphic Computations for FHE-Based Applications

Uses Software

• HElib
• TASTY
• FHEW
• GitHub
• fhe
• TinyGarble

Cites Work

• (Leveled) Fully Homomorphic Encryption without Bootstrapping
• Fixed-point arithmetic in SHE schemes
• Group homomorphic encryption: characterizations, impossibility results, and applications
• Homomorphic Encryption from Learning with Errors: Conceptually-Simpler, Asymptotically-Faster, Attribute-Based
• Public Key Compression and Modulus Switching for Fully Homomorphic Encryption over the Integers
• Homomorphic Evaluation of the AES Circuit
• FHEW: Bootstrapping Homomorphic Encryption in Less Than a Second
• Fully Homomorphic Encryption with Relatively Small Key and Ciphertext Sizes
• Fully Homomorphic Encryption over the Integers
• ML Confidential: Machine Learning on Encrypted Data
• Fully homomorphic encryption using ideal lattices
• Scale-Invariant Fully Homomorphic Encryption over the Integers
• Efficient Fully Homomorphic Encryption from (Standard) LWE

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